Introduction
Choosing the right database for your application is a crucial decision that impacts performance, scalability, and cost. AWS offers multiple database solutions, but two of the most commonly used ones are Amazon RDS and Amazon DynamoDB. While both are fully managed by AWS, they cater to different use cases based on whether your application needs structured, relational data or high-performance NoSQL storage.
In this blog, we will explore the differences between AWS RDS vs DynamoDB, covering their features, performance, pricing, and ideal use cases to help you make an informed decision.
What is AWS RDS?
AWS Relational Database Service (RDS) is a fully managed database service that allows developers to set up, operate, and scale relational databases in the cloud with minimal effort. RDS supports multiple relational database engines, including:
- MySQL
- PostgreSQL
- MariaDB
- Oracle
- Microsoft SQL Server
- Amazon Aurora (AWS’s own high-performance relational database)
Key Features of AWS RDS
- Managed Service – AWS handles backups, patching, and monitoring.
- Multi-AZ Deployment – Provides high availability and automatic failover.
- Read Replicas – Improves read performance by distributing traffic across multiple copies of the database.
- Automatic Backups – Supports point-in-time recovery and scheduled backups.
- Customizable Compute and Storage – Allows vertical scaling of resources based on demand.
- SQL Support – Uses traditional relational database queries.
What is AWS DynamoDB?
AWS DynamoDB is a fully managed NoSQL database service that provides high performance and scalability. Unlike RDS, DynamoDB is designed for key-value and document-based data models, making it ideal for applications requiring low-latency and high-speed access.
Key Features of AWS DynamoDB
- Serverless Architecture – No need to manage infrastructure, and it scales automatically.
- High Availability – Data is automatically replicated across multiple AWS Availability Zones.
- Single-Digit Millisecond Latency – Ideal for real-time applications.
- Pay-Per-Request Pricing Model – Costs are based on read/write throughput rather than instance size.
- Supports Key-Value and Document Storage – Provides flexibility for storing different types of data.
- Built-in Security and Compliance – Integrated with AWS Identity and Access Management (IAM) and encryption features.
Performance Comparison
The choice between RDS and DynamoDB largely depends on how your application accesses and processes data.
AWS RDS Performance
- Best suited for structured data where relationships and transactions are crucial.
- Uses SQL-based queries, which can be optimized for indexing, joins, and aggregations.
- Performance scales vertically by increasing instance sizes or using read replicas for high-read workloads.
- Has higher latency compared to DynamoDB when handling real-time requests.
AWS DynamoDB Performance
- Optimized for high-speed, real-time applications.
- Scales horizontally by distributing data across multiple partitions.
- No need for schema design, making it flexible for dynamic and large-scale applications.
- Provides single-digit millisecond latency for read and write operations.
Cost Comparison
AWS RDS Pricing
- Billed based on instance size, storage, and data transfer.
- Additional costs for backups, Multi-AZ deployments, and read replicas.
- Suitable for applications with consistent and predictable workloads.
AWS DynamoDB Pricing
- Pay-as-you-go pricing model based on read/write requests and storage.
- Supports on-demand capacity mode (pay for requests) and provisioned mode (pay for fixed throughput).
- Ideal for applications with fluctuating traffic, as costs scale dynamically.
Key Differences: AWS RDS vs. DynamoDB
| Feature | AWS RDS | AWS DynamoDB |
| Data Model | Relational (SQL-based) | NoSQL (Key-Value, Document) |
| Scalability | Vertical & Read Replicas | Horizontal (Automatic Scaling) |
| Query Language | SQL | NoSQL API |
| Use Case | Transactional applications, ERP, CRM | Real-time analytics, IoT, gaming |
| Backup & Recovery | Automated backups, snapshots | Point-in-time recovery |
| Performance | Optimized for structured queries | Optimized for high-speed access |
| Cost Model | Pay for instance & storage | Pay-per-request pricing model |
When to Use AWS RDS
You should choose AWS RDS if:
- Your application requires structured, transactional data.
- You need ACID compliance for consistency and reliability.
- Your workload includes complex queries, joins, and aggregations.
- You prefer traditional SQL-based database management.
- You need enterprise applications like ERP, CRM, and financial systems.
When to Use AWS DynamoDB
You should choose AWS DynamoDB if:
- Your application requires high-speed, real-time data access.
- You work with unstructured or semi-structured data.
- Your workload has high read/write throughput and unpredictable traffic.
- You want a serverless database with automatic scaling.
- Your use case includes IoT applications, gaming, or e-commerce platforms.
Conclusion
AWS RDS and DynamoDB cater to different database needs. RDS is best suited for structured, transactional data, whereas DynamoDB is designed for high-speed, scalable NoSQL applications. Your choice should depend on your application’s data model, query patterns, scalability needs, and budget considerations.
For many businesses, a hybrid approach may be ideal, where transactional data is stored in RDS while high-velocity, real-time data is handled by DynamoDB.
Still not sure which database is right for you? Contact us for expert guidance on AWS database solutions!